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Reseach Article

Parallel Computing for Analysis of Large Scale Social Network

by Badrun Nahar Khan, Noor Mohammad Zahid
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 24
Year of Publication: 2018
Authors: Badrun Nahar Khan, Noor Mohammad Zahid
10.5120/ijca2018917972

Badrun Nahar Khan, Noor Mohammad Zahid . Parallel Computing for Analysis of Large Scale Social Network. International Journal of Computer Applications. 181, 24 ( Oct 2018), 17-18. DOI=10.5120/ijca2018917972

@article{ 10.5120/ijca2018917972,
author = { Badrun Nahar Khan, Noor Mohammad Zahid },
title = { Parallel Computing for Analysis of Large Scale Social Network },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2018 },
volume = { 181 },
number = { 24 },
month = { Oct },
year = { 2018 },
issn = { 0975-8887 },
pages = { 17-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number24/30032-2018917972/ },
doi = { 10.5120/ijca2018917972 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:06:55.695738+05:30
%A Badrun Nahar Khan
%A Noor Mohammad Zahid
%T Parallel Computing for Analysis of Large Scale Social Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 24
%P 17-18
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The importance of social network analysis is realized as an inevitable tool in forthcoming years. This is due to the unprecedented growth of social-related data, boosted by the proliferation of social media websites and the embedded heterogeneity and complexity. The data generated from social network 10-15% data among them are structured and 85-90% data are unstructured. The unstructured data are useless. We will need additional technique to process those unstructured data. This paper focuses on parallel computational techniques for social network analysis. In particular, a brief discussion of some existing parallel algorithms is carried out and a new parallel computational technique is proposed to achieve parallelism.

References
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  5. George Cybenko, Parallel Computing for Machine Learning in Social Network Analysis
Index Terms

Computer Science
Information Sciences

Keywords

Parallelism vertices edges graph architecture and so on.